See also this post for brief notes on:
  • Ross Anderson | Security Engineering
  • David Christian | Origin Story: A Big History of Everything
  • Richard Feynman | The Character of Physical Law  
  • Richard Feynman | The Feynman Lectures on Physics
  • Jessica Livingston | Founders at Work
  • Walter Scheidel | The Great Leveler: Violence and the History of Inequality
  • Thomas Schelling | The Strategy of Conflict



  • Greg Egan | Diaspora
    • A wild and very well thought-out ride through a far-future world, featuring fictional physics theories plausible enough that they may one day win a Nobel. 
  • Greg Egan | Permutation City
    • This book is mostly a sustained thought experiment that extrapolates crazy but internally consistent conclusions from its philosophical premises.
  • Neal Stephenson | The Baroque Cycle (consists of Quicksilver, The Confusion, and The System of the World) 
    • An expansive story about science, finance, politics, and alchemy in the late 1600s and early 1700s. Almost every natural philosopher of the time makes an appearance, with Newton, Leibniz, and Hooke each being significant characters. It's published as a trilogy, but reads more like a single gargantuan novel.

See also this post for brief notes on:
  • Scott Alexander | Unsong
  • Lois McMaster Bujold | The Curse of Chalion
  • Ted Chiang | Exhalation
  • Hannu Rajaniemi | Summerland 
  • Neal Stephenson | Cryptonomicon


  • Growth and civilisation
    • A constantly expanding economy is one reason why societal norms and moral values have shifted for the better. If growth ceases, a reversion from norms of value-creation and tolerance back to norms of capturing value from others and defending your own in-group is possible in the long run.
  • EA ideas 1: rigour and opportunity in charity
    • Effective altruism is about carefully reasoning how to do the most good. A focus on impartial welfarist good, the effectiveness of our efforts, and open-minded uncertainty-acknowledging reasoning leads to a different picture of charity than the usual, but also one that is more likely to do good.
  • EA ideas 2: expected value and risk neutrality
    • A rational agent maximises the expected value of what it cares about. Expected value reasoning is not free of problems, but, outside extreme thought experiments and applied carefully, it clears most of them, including "Pascal's mugging" (high-stakes, low-probability situations). Expected value reasoning implies risk neutrality. The most effective charity may often be a risky one, and gains from giving may be dominated by a few risky bets.
  • EA ideas 3: uncertainty
    • We are uncertain about both what is right and what is true (being mindful of the difference is often important). Moral uncertainty raises the question of how we should act when we have credence in more than one moral theory. Uncertainty about truth has many sources, including ones broader than uncertainty about specific facts, such as our biases or the difficulty of confirming some facts. These uncertainties suggest we are unaware of huge problems and opportunities.
  • EA ideas 4: utilitarianism
    • While not a necessary part of EA thinking, utilitarianism is the most successful description of the core of human ethics so far. In principle (if not practice, due to the complexity of defining utility), it is capable of deciding every moral question, an important property for a moral system. Our moral progress over the past few centuries can be summarised as a transition to more utilitarian morality.


  • Two proofs
    • Two accessible, visual, and (dare I say it?) fun proofs of simple mathematical results.
  • Classical physics
    • A summary of the form, gist, and "character" of all fundamental laws of classical physics.
  • Data science 1
    • Notes on fundamental data science concepts (notation; some probability laws; maximum likelihood estimation; supervised and unsupervised learning; fitting, interpreting, and visualising linear models; empirical distributions; KL divergence).
  • Data science 2
    • More data science notes (Monte Carlo methods; Bayesianism and frequentism; randomised computational methods for Bayesian and frequentist calculations; Markov's, Chebyshev's, and Jensen's inequalities; causal diagrams; Markov chains).


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